Contemporary Patterns of Care for Low-Grade Glioma in Australia and New Zealand
Bibliographic record
Abstract
AIM: study highlighted the benefits of an IDH inhibitor, vorasidenib, in treating residual or recurrent grade 2 IDH-mutant gliomas following surgery alone. We aimed to characterise the current patterns of care for patients with LGGs in Australia and New Zealand, including the role of vorasidenib. METHODS: An online survey examining respondents' practice setting, caseload, and preferred treatment approach to three clinical scenarios was distributed through the Cooperative Trials Group for Neuro-Oncology, New Zealand Aotearoa Neuro-Oncology Society, and the Australian and New Zealand Society for Neuropathology in December 2023 with three reminders in April, June, and September of 2024. RESULTS: The survey response rate was 19.6% (57/291), 87.7% from Australia, and 12.3% from New Zealand, spanning medical oncology (45.7%), pathology (22.8%), radiation oncology (17.5%), and neurosurgery (14.0%). Case 1 examined an IDH-mutant grade 2 astrocytoma following gross total resection. Observation alone was recommended by 93%. Case 2 examined an incompletely resected IDH-mutant grade 2 astrocytoma. If feasible, 38% recommended further surgery and 83% adjuvant chemotherapy and radiotherapy. After 12 months of disease stability, 53% of the respondents preferred vorasidenib over the existing therapies. Case 3 examined an incompletely resected IDH-mutant grade 3 oligodendroglioma. No respondents recommended observation alone, with 26% recommending salvage surgery and 97% recommending further chemotherapy and radiotherapy. CONCLUSIONS: This study describes current management practices for LGGs in Australia and New Zealand, showing ongoing variation and a cautious approach to integrating IDH inhibitors. This highlights the critical role of multidisciplinary team-based decision-making in increasingly complex clinical situations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".